VIF-based adaptive matrix perturbation method for heteroskedasticity-robust covariance estimators in the presence of multicollinearity

DOI10.1080/03610926.2015.1060340zbMath1368.62194OpenAlexW2340922188MaRDI QIDQ4976207

Chien-Chia Liäm Huang, Hsun-Jung Cho, Yow-Jen Jou

Publication date: 27 July 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2015.1060340

zbMATH Keywords

optimizationmatrix theorylinear regressioncollinearity

Mathematics Subject Classification ID

Linear regression; mixed models (62J05) Diagnostics, and linear inference and regression (62J20)

Related Items (1)

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Cites Work

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• Generalized autoregressive conditional heteroscedasticity
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• Inequalities for the trace of matrix product
• Using Liu-Type Estimator to Combat Collinearity
• VIF Regression: A Fast Regression Algorithm for Large Data
• Performance of Kibria's Method for the Heteroscedastic Ridge Regression Model: Some Monte Carlo Evidence
• Inference Under Heteroskedasticity and Leveraged Data

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